A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture
Clustering is a fundamental problem in many data-driven application domains, and clustering performance highly depends on the quality of data representation. Hence, linear or non-linear feature transformations have been extensively used to learn a better data representation for clustering. In recent...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8412085/ |
| _version_ | 1819169213363781632 |
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| author | Erxue Min Xifeng Guo Qiang Liu Gen Zhang Jianjing Cui Jun Long |
| author_facet | Erxue Min Xifeng Guo Qiang Liu Gen Zhang Jianjing Cui Jun Long |
| author_sort | Erxue Min |
| collection | DOAJ |
| description | Clustering is a fundamental problem in many data-driven application domains, and clustering performance highly depends on the quality of data representation. Hence, linear or non-linear feature transformations have been extensively used to learn a better data representation for clustering. In recent years, a lot of works focused on using deep neural networks to learn a clustering-friendly representation, resulting in a significant increase of clustering performance. In this paper, we give a systematic survey of clustering with deep learning in views of architecture. Specifically, we first introduce the preliminary knowledge for better understanding of this field. Then, a taxonomy of clustering with deep learning is proposed and some representative methods are introduced. Finally, we propose some interesting future opportunities of clustering with deep learning and give some conclusion remarks. |
| first_indexed | 2024-12-22T19:15:55Z |
| format | Article |
| id | doaj.art-b9b3170fbe81476eba202d284eea0ace |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T19:15:55Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-b9b3170fbe81476eba202d284eea0ace2022-12-21T18:15:31ZengIEEEIEEE Access2169-35362018-01-016395013951410.1109/ACCESS.2018.28554378412085A Survey of Clustering With Deep Learning: From the Perspective of Network ArchitectureErxue Min0https://orcid.org/0000-0002-1972-6608Xifeng Guo1Qiang Liu2https://orcid.org/0000-0003-2922-3518Gen Zhang3https://orcid.org/0000-0001-7709-0751Jianjing Cui4Jun Long5College of Computer, National University of Defense Technology, Changsha, ChinaCollege of Computer, National University of Defense Technology, Changsha, ChinaCollege of Computer, National University of Defense Technology, Changsha, ChinaCollege of Computer, National University of Defense Technology, Changsha, ChinaCollege of Computer, National University of Defense Technology, Changsha, ChinaCollege of Computer, National University of Defense Technology, Changsha, ChinaClustering is a fundamental problem in many data-driven application domains, and clustering performance highly depends on the quality of data representation. Hence, linear or non-linear feature transformations have been extensively used to learn a better data representation for clustering. In recent years, a lot of works focused on using deep neural networks to learn a clustering-friendly representation, resulting in a significant increase of clustering performance. In this paper, we give a systematic survey of clustering with deep learning in views of architecture. Specifically, we first introduce the preliminary knowledge for better understanding of this field. Then, a taxonomy of clustering with deep learning is proposed and some representative methods are introduced. Finally, we propose some interesting future opportunities of clustering with deep learning and give some conclusion remarks.https://ieeexplore.ieee.org/document/8412085/Clusteringdeep learningdata representationnetwork architecture |
| spellingShingle | Erxue Min Xifeng Guo Qiang Liu Gen Zhang Jianjing Cui Jun Long A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture IEEE Access Clustering deep learning data representation network architecture |
| title | A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture |
| title_full | A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture |
| title_fullStr | A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture |
| title_full_unstemmed | A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture |
| title_short | A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture |
| title_sort | survey of clustering with deep learning from the perspective of network architecture |
| topic | Clustering deep learning data representation network architecture |
| url | https://ieeexplore.ieee.org/document/8412085/ |
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